COSTA, M. N. M.; http://lattes.cnpq.br/4053682788696455; COSTA, Milla Nóbrega de Menezes.
Résumé:
Environmental factors contribute to atmospneric instability in any part of the globe. It is
extremely important to understand them, as these factors are vital to concise weather
forecasting. The state of Paraíba has been shidied scientifically due to its rainfall
irreguiarities; however, there are stilt few studies on how meteorological systems act on the vertical síruciure u f íhe aíinospíiere o f íhis region, anu iheir coiisequeriuv hartniiig effecís on climatological forecasts. This work aims to characterize the structure o f the atmosphere of Paraíba in order to expand the scarce scientific knowledge on it by using data from tlie reanalysis applied to the computational program in the language Python. Cities were selected tíi uiffeiciii iíiesoíegioiis of the state, such as Alhandra (coastal), Areia (brejo - wetlaiids), Campina Grande (agreste - semi moist), Taperoá (Cariri - dry) and Catolé do Rocha (Sertão - backlands). For the present study, monthly observationaí data on precipitation were used between 1980 - 2016 and 2016; whereas daily data were provided by the Executive Agency resolution 0.125 ° X 0.125, which were obtained from the European Center for Médium Range Weather Forecasting (ECMWF), as well as from GOES 13 satellite images provided by the National Institute for Space Research in partnership with the Center for Weather at the pressure leveis: 1000, 850, 700, 500, 200mb) that were plotted. The Wavelet Analysis methodology with its monthly data was applied in addition to daily data, atmospheric structure verification equations, instability índices, and the SHARPpy program (Skew-T and program data. This program was used as a test for the present work. The results showed that, between 1980 and 2016, the annual cycle revealed a 95% assurance in relation to precipitation versus time. However, the smaller scales, 0.25 (intrasazonal, 1 to 2 months), greater than 0.25 that higher precipitation is concentrated on these scales. The histograms reveal that the observed mean data and reanalysis data can capture equivalent information, thus validating the use of surface and upper air reanalysis data in the present study. However, it is worth the meteorological aspects on each specífic day that was selected revealed the influence of
several meteorological systems such as High Subtropical, High of Bolívia, High of the
Azores, ITCZ, VCAN, convective system, among others. And the SHARPpy program that
was used as a test to analyze the configuration of the aUnosphere structure for the cities on the selected days in the work, allowed the identification of meteorological systems that were acting and influencing the atmosphere at great, meso and micro scales under conditions of precipitation or not. Thus, it has displayed coherence as to its results, in the sense that the profíle of the atmosphere was representative of the weather conditions. Therefore, interaction between active systems was detected, indicating coupling between them. And the orography was found to be of greater importance and impactful considering the vertical profíle of thelocal atmosphere.